code: def initialize_device_mesh(
      world_size: int = -1,
      physical_devices: List[int] = None,
      alpha_beta_dict: Dict[Tuple[int], Tuple[float]] = None,
      logical_mesh_shape: Tuple[int] = None,
      logical_mesh_id: torch.Tensor = None,
  ):
      """
      This method is used to initialize the device mesh.
  
      Args:
          world_size: the size of device mesh. If the world_size is -1,
              the world size will be set to the number of GPUs in the current machine.
          physical_devices: the physical devices used to initialize the device mesh.
          alpha_beta_dict(optional): the alpha_beta_dict contains the alpha and beta values
              for each devices. if the alpha_beta_dict is None, the alpha_beta_dict will be
              generated by profile_alpha_beta function.
          logical_mesh_shape(optional): the logical_mesh_shape is used to specify the logical
              mesh shape.
          logical_mesh_id(optional): the logical_mesh_id is used to specify the logical mesh id.
      """
      # if world_size is not set, use the world size from torch.distributed
      if world_size == -1:
          world_size = dist.get_world_size()
  
      if physical_devices is None:
          physical_devices = [i for i in range(world_size)]
      physical_mesh = torch.tensor(physical_devices)
  
      if alpha_beta_dict is None:
          # if alpha_beta_dict is not given, use a series of executions to profile alpha and beta values for each device
          ab_profiler = AlphaBetaProfiler(physical_devices)
          alpha_beta_dict = ab_profiler.alpha_beta_dict
      else:
          ab_profiler = AlphaBetaProfiler(
              physical_devices, alpha_beta_dict=alpha_beta_dict
          )
  
      if logical_mesh_shape is None and logical_mesh_id is None:
          # search for the best logical mesh shape
          logical_mesh_id = ab_profiler.search_best_logical_mesh()
          logical_mesh_id = torch.Tensor(logical_mesh_id).to(torch.int)
          logical_mesh_shape = logical_mesh_id.shape
  
          # extract alpha and beta values for the chosen logical mesh shape
          (
              mesh_alpha,
              mesh_beta,
          ) = ab_profiler.extract_alpha_beta_for_device_mesh()
  
      elif logical_mesh_shape is not None and logical_mesh_id is None:
          logical_mesh_id = physical_mesh.reshape(logical_mesh_shape)
  
          # extract alpha and beta values for the chosen logical mesh shape
          mesh_alpha, mesh_beta = extract_alpha_beta_for_device_mesh(
              alpha_beta_dict, logical_mesh_id
          )
  
      device_mesh = DeviceMesh(
          physical_mesh_id=physical_mesh,
          logical_mesh_id=logical_mesh_id,
          mesh_alpha=mesh_alpha,
          mesh_beta=mesh_beta,
          init_process_group=True,
      )
      return device_mesh
  
imports: from typing import Dict, List, Tuple
  import torch
  import torch.distributed
  import torch.nn
  from torch.fx.graph import Graph
  from colossalai._analyzer.fx.codegen import ActivationCheckpointCodeGen
  from colossalai._analyzer.fx.graph_module import ColoGraphModule
  from colossalai._analyzer.fx.passes import shape_prop_pass
  from colossalai._analyzer.fx.tracer.tracer import ColoTracer
  from colossalai.auto_parallel.passes.runtime_apply_pass import runtime_apply_pass
  from colossalai.auto_parallel.passes.runtime_preparation_pass import runtime_preparation_pass
  from colossalai.auto_parallel.tensor_shard.options import DataloaderOption, ShardOption, SolverOptions, SolverPerference
  from colossalai.auto_parallel.tensor_shard.sharding_strategy import CommAction
  from colossalai.auto_parallel.tensor_shard.solver import CostGraph, Solver, StrategiesConstructor
  from colossalai.device.alpha_beta_profiler import AlphaBetaProfiler
  from colossalai.device.device_mesh import DeviceMesh
  from colossalai.tensor.sharding_spec import ShardingSpec
label_desc: Use image node_id 6 for calling a global function with example usage: initialize_device_mesh(world_size, physical_devices, alpha_beta_dict, logical_mesh_shape, logical_mesh_id) and returns: device_mesh